Due to exponential growth of LTE traffic, mobile operators are spending hundreds of millions of dollars improving their cellular infrastructure. Different capacity improvement and congestion mitigation approaches include spending major capital to acquire new spectrum, building new macro sites to add bandwidth, and building small cells as well as in-building solutions. These approaches have proven effective in certain cases but are expensive and not always practical when facing challenges associated with dynamic capacity demands. When facing dynamic capacity demands and in the absence practically viable systematic optimization approaches, mobile operators exercise manual fine-tuning of cellular network parameters in order to alleviate cellular congestion. However, the results are trivially suboptimal compared to systematic optimization approaches. This invention presents systematic approaches to optimally reduce the congestion of LTE networks.
The capacity challenge in LTE networks is better understood by explaining how resources are allocated to users. Under LTE standard, each cellular tower has a fixed number of Physical Resource Blocks (PRBs) defined in time and frequency. Utilization of each PRB is independent of utilization of other PRBs within the same cell without causing interfere. When a user requests a certain type of service or Enhanced Radio Access Bearer (ERAB), the LTE scheduler at a cell-site will allocate a certain number of PRBs depending on the type of service, i.e., guaranteed bit rate versus non-guaranteed bit rate, required bandwidth, required latency, and most importantly the maximum throughput that can be carried. This throughput associated with each PRB mainly depends on the maximum allowable modulation scheme ranging from QPSK at the lowest level to 16QAM and up to 64QAM. The maximum allowable modulation depends on the Signal to Interference and Noise Ratio (SINR) experienced by a given user for that PRB. For example, a user requesting video streaming while experiencing excellent RF conditions and hence high SINRs will be able to use high modulation schemes such as 64QAM per each PRB assigned and will hence require a small number of PRBs to satisfy its requested ERAB. On the other hand, a user experiencing sub-par RF conditions and hence poor SINRs will only be able to utilize low modulation schemes such as QPSK hence requiring a much larger number of PRBs than the previous user in order to satisfy a similar video streaming quality [8].
FIG. 1 captures the relationship among LTE Channel Quality Indicator (CQI), modulation, coding rate, spectral efficiency, achievable throughput per PRB, and SINR. Aside from the utilization of techniques such as Multi Input Multi Output (MIMO) and Inter-Cell Interference Coordination (ICIC) [8] to mitigate sub-par RF conditions and improve SINR, the physical limitation on the number of available PRB s still presents a challenge required to be addressed in heavily loaded scenarios of operations. Depending on the bandwidth of an LTE channel, each cell offers a fixed number of PRBs. For example, a 5 MHz and a 10 MHz LTE channel offer no more than 25 and 50 PRB s. When the demand for PRB s is higher than what a cell can offer, adverse impacts on User Equipment (UEs) connected to the cell may be imposed. The impacts range from degrading the speed of existing connections, denying incoming handover requests, or even dropping calls in severe cases of congestion. Since LTE systems only support hard handovers and all cellular towers operate on the same frequency, a UE remains connected to its original cellular tower if denied a handover request. Therefore, it can be heavily interfered with by the new cellular tower causing severe quality degradation and eventually a call drop [8].
In order to mitigate the issue noted above, most operators attempt at keeping per cell PRB utilization under a congestion threshold of 80%. The reserved 20% capacity of the cell can then be used to service handover requests and provide a safety margin to avoid denial of handover requests. Cells exceeding the congestion threshold usually trigger augmentation mechanisms such as carrier additions or bandwidth expansions. In an effort to keep PRB utilization under the limit of 80%, it is critical to manage traffic amongst various cells where traffic from highly loaded cells is offloaded to lightly loaded cells serving the same area. This traffic offload can be achieved in several manners, i.e., by changing the footprint of cells, shifting cell boundaries, and changing tilts as well as azimuths of cells. However, implementing physical changes is time consuming and more suited for static or slowly changing environments as oppose to fast changing dynamic environments.
Alternatively, this invention introduces changing the power of a cell i referred to as i and handover threshold of a cell i referred to as i in order to control the serving area of said cell and redistribute traffic as needed. These parameters can be changed instantly in the field in response to dynamic changes in traffic distributions in order to offload traffic from congested cells to neighboring cells. Caution has to be exercised such that traffic offloading is done without congesting the neighboring cells and without degrading the quality of the UEs on the edge of congested cells that end up shifting to a neighboring cell.
The phrases cell, cell tower, and cellular tower are used interchangeably in the disclosure of this invention.